Segmentation Analysis of Domestic Tourists Visiting Banyuwangi's Region Based Travel Behavior Aspect Using Clustering Method

Abstract

The increasing population mobility as tourists, then accurate calculations based on quantitative data are needed to find out the trends that will occur. The amount of data that is large and varied, then used a quantitative segmentation technique, namely clustering k-means, based on the variable travel behavior. The sampling technique used was accidental sampling with 90 respondents taken from 3 tourist sites in Banyuwangi, namely Sidodadi Glenmore Reservoir, Marina Boom, and Bangsring Underwater. From clustering k-means formed 5 segments of tourists visiting Banyuwangi.